Does creatine cause hair loss? A 12-week randomized controlled trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Creatine is a widely used ergogenic aid that enhances muscle strength and lean mass. However, concerns have been raised about the potential role in promoting hair loss by increasing dihydrotestosterone (DHT). Currently, there is no direct evidence examining the relationship between creatine supplementation and hair follicle health. Therefore, the purpose was to determine the effects of 12 weeks of creatine supplementation on androgen levels and hair follicle health in healthy young males. METHODS: Forty-five resistance-trained males (ages 18-40 years) were recruited and randomly assigned to either a creatine monohydrate (5 g/day) or placebo (5 g maltodextrin/day) group. Participants maintained their habitual diets and training routines. Blood samples were collected at baseline and after 12 weeks to measure total testosterone, free testosterone, and DHT. Hair follicle health was assessed using the Trichogram test and the FotoFinder system (hair density, follicular unit count, and cumulative hair thickness). Statistical analyses were performed using repeated measures ANOVA, and potential outliers were examined through sensitivity analysis. RESULTS: > 0.05). While total testosterone increased (∆ = post value minus pre value: creatine = ∆124 ± 149 ng/dL; placebo = ∆216 ± 203 ng/dL) and free testosterone decreased (creatine = ∆-9.0 ± 8.7 pg/mL; placebo = ∆-9 ± 6.4 pg/mL) over time, these effects were independent of supplementation. There were no significant differences in DHT levels, DHT-to-testosterone ratio, or hair growth parameters between the creatine and placebo groups. CONCLUSION: This study was the first to directly assess hair follicle health following creatine supplementation, providing strong evidence against the claim that creatine contributes to hair loss.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it